A confusion matrix can help you identify the types and sources of errors your model makes, while a classification report can help you evaluate the quality and reliability of your model.

A binary classification model is a type of machine learning algorithm that predicts whether an input belongs to one of two possible classes, such as spam or not spam, positive or negative, etc.

The reason that the confusion matrix is particularly useful is that, unlike other types of classification metrics such as simple accuracy, the confusion matrix generates a more complete picture of how ...

Specially challenging is the task of plotting multiclass classification results as they involve categorical variables (classes) rather than numeric ... are commonly summarized in the form of a ...

Abstract: EEG signals exhibit non-stationary characteristics, particularly across different subjects, which presents significant challenges in the precise classification of mental workload levels when ...